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Diagnosing surgical site infections using telemedicine: A Systematic Review

Diagnosing surgical site infections using telemedicine: A Systematic Review

Surgeon. 2021 Jun 19:S1479-666X(21)00101-3. doi: 10.1016/j.surge.2021.05.004. Online ahead of print.

ABSTRACT

BACKGROUND: Surgical site infections (SSI) are preventable post-operative complications. With the increase in use of telehealth modalities, there is a need to assess if telehealth modalities are safe for assessment of SSI.

AIM: This review aims to assess the accuracy of using telemedicine in the diagnosis of SSI in post-surgical adult patients as compared to in-person assessments.

METHODS: A comprehensive search on 6 databases (PubMed, MEDLINE, Embase, Web of Science, Scopus and CENTRAL) was performed from inception to 1 December 2020. Data was extracted to determine accuracy, feasibility, acceptability, and usability of using telemedicine to detect SSIs. The primary outcome of this review was to review the diagnostic accuracy of telemedicine to diagnose SSIs as compared to direct, in-person assessment. Methodological quality was evaluated using the MINORS criteria.

RESULTS: Six studies met inclusion criteria. Results were summarized qualitatively. The overall methodological quality of the studies was moderate based on the MINORS score. Four studies utilized telephone surveillance, whilst two utilized mobile applications. Telemedicine modalities were able to accurately diagnose 66 SSIs, where an additional 15 were found on direct clinical review. The diagnostic accuracy across the studies ranged from 69.5 to 100%. Between 82.5 and 100% of patients were able to be contacted through these telemedicine modalities.

CONCLUSIONS: Telemedicine modalities are a feasible option for post-operative follow-up, especially in the identification of SSIs. As technology becomes more affordable and widely available, future applications of telemedicine are limitless. However, further research is still required to ensure that telemedicine is a safe and effective tool.

PMID:34158250 | DOI:10.1016/j.surge.2021.05.004

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